According to the trajectory reappearance and feature expression of pedestrian movement, based on video processing, a pedestrian feature extraction and tracking algorithm combining with temporal and spatial context information is proposed. Then the center offset is introduced into the calibration to overcome the shortcomings of the collinear model which does not consider the lens distortion, thus the calibration precision is improved. This algorithm is used to obtain some groups of pedestrian movement parameters and trajectory curve on real video processing. Then the data extracted by this algorithm is compared with both the data calculated through the collinear calibration method and the real data from artificial investigation, in order to verify the accuracy of this algorithm. Finally, several pedestrian crossing behaviors are quantitatively analyzed and the corresponding feature statuses are expressed, which can support the organization and control of pedestrian traffic.